newGS

说明：  可对lytro相机所得到的光场图像进行各种处理(The light field image obtained by lytro camera can be processed in various ways.)

将一幅M×N的灰度图像用3×3平均滤波器进行模糊，分别再加上一定的高斯 噪声和均匀噪声。然后，设计一个维纳滤波器对这两幅图像进行复原，分别 计算这两幅图像复原前后的PSNR。(Gray-scale image of a MN 33 average filter is vague, respectively, plus a Gaussian noise and uniform noise. Then, design a Wiener filter to recover these two images, the two images before and after the recovery of PSNR were calculated.)

RunSFM中作者写的纹理映射的应用程序(RunSFM the authors write texture mapping application)

下面给出了48项泽尼克多项式，外加一项常数项。需要注意的是，读者并不需要严格按照下文所示的顺序排列这些泽尼克项，实际上在不同的应用和机构会采用不同的排列顺序。 表中的#0项是个常数或者说是平移项（piston term），这一项的系数也代表了平均光程差；而#1和#2项分别是x和y方向的倾斜项（tilt terms），#3代表了聚焦，因此，#1到#3项代表了波前的高斯或者近轴特性；#4和#5项代表了像散和离焦，#6和#7项代表彗差和倾斜，而#8项代表了3级像差和离焦，也就是说#4到#8项为3级相差项；同样地，#9到#15项代表了5级像差，而#16到#24项代表了7级像差，#25到#35项代表了9级像差，#36到#48项代表了11级像差。(Here are 48 Zernike polynomials, plus a constant term. It is important to note that the reader does not need to strictly arrange the Zernike entries in the order shown below, but in fact different orders of arrangement are applied to different applications and institutions. Table #0 is a constant or a shift (piston term), a coefficient of this term also represents the average optical path difference; while #1 and #2 are inclined X and Y direction (tilt terms), #3 represents the focus, therefore, #1 to #3 on behalf of the wavefront. Gauss or paraxial properties; #4 and #5 represent the astigmatism and defocus, #6 and #7 represent coma and tilt, and #8 represents the 3 order aberration and defocus, that is to say #4 to #8 is 3 level difference; similarly, #9 to #15 on behalf of the 5 order aberration #16 and #24, to represent the 7 level #25 to #35 aberration, on behalf of the 9 #36 to #48 aberration, on behalf of the 11 order aberration.)

基于互相关的图像配准程序，能实现亚像素级的配准(Sub pixel level registration based on cross correlation image registration process)

说明：  如题，matlab手写数字测试图像处理 样本（30+50个）加全代码加测试结果(Like title, matlab handwritten digital test image processing samples (30 + 50) plus full code plus test results)

颜色特征提取，为matlab 源文件，是底层图像处理的基本特征之一，是本人在做硕士论文时收集修改的代码(Color Feature Extraction for the matlab source file, the underlying image processing are one of the essential features)

说明：  经典的粒子滤波算法，适用于粒子滤波的初学者更好的了解粒子滤波(Classical particle filter, particle filter for better understanding of particle filter for beginners)

西安科技大学，图像处理教程的课件，做成了PDF格式，希望对你们有用(Xi' an University of Technology, image processing tutorial courseware, made the PDF format, hope that is helpful for you)

说明：  1. 对图像进行傅里叶变换。 2. 根据傅里叶变换的结果去除图像的竖条纹噪声。 3. 对图像进行傅里叶逆变换，得到分割图像。 (1. For the image Fourier transform. 2. According to the results of Fourier transform to remove the image of the vertical stripe noise. 3. Inverse Fourier Transform of the images obtained segmented image.)